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| http://dx.doi.org/10.1200/CCI.20.00086 | DOI Listing |
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Diagnostic performance of biomarkers for differentiating active tuberculosis from latent tuberculosis: a systematic review and Bayesian network meta-analysis.
Front Microbiol
December 2024
Department of Laboratory Medicine, Daejeon Eulji Medical Center, Eulji University, Daejeon, Republic of Korea.
Background: PCR and culture tests are used together to confirm the diagnosis of active tuberculosis (TB). Due to the long culture period, if the PCR test is negative, it takes a significant amount of time for the culture result to be available. Interferon- release assays (IGRAs), which are widely used to diagnose TB or latent tuberculosis infection (LTBI), cannot effectively discriminate TB from LTBI.
View Article and Find Full Text PDFIntegration of pharmacogenetic data in epic genomic module drives clinical decision support alerts.
Front Pharmacol
December 2024
Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States.
Introduction: The Precision Medicine Program (PMP) at the University of Florida (UF) focuses on advancing pharmacogenomics (PGx) to improve patient care.
Methods: The UF PMP, in collaboration with the UF Health Pathology Laboratory (UFHPL), utilized Health Level Seven (HL7) standards to integrate PGx data into Epic's Genomic Module to enhance the management and utilization of PGx data in clinical practice.
Results: A key feature of the Genomic Module is the introduction of genomic indicators-innovative tools that flag actionable genetic information directly within the electronic health record (EHR).
Zellweger syndrome; identification of mutations in and gene in Saudi families.
Ann Med
December 2025
Department of Basic Medical Sciences, College of Medicine & Center for Genetics and Inherited Diseases, Taibah University Medina, Medina, Saudi Arabia.
Background: Peroxisome biogenesis disorders (PBD) affect multiple organ systems. It is characterized by neurological dysfunction, hypotonia, ocular anomalies, craniofacial abnormalities, and absence of peroxisomes in fibroblasts. PBDs are associated with mutations in any of fourteen different genes, which are involved in peroxisome biogenesis.
View Article and Find Full Text PDFGenomic Surveillance of Foodborne Pathogens: Advances and Obstacles.
J Public Health Manag Pract
November 2024
Author Affiliations: Microbiology, Human Foods Program, US Food and Drug Administration, College Park, Maryland (Gensheimer, Allard, Timme, Brown, Hintz, Pettengill, Strain, Tallent, Vélez); and Association of Public Health Laboratories, Bethesda, Maryland (King, Shea).
Context: The genomic surveillance of foodborne pathogens in the United States has grown exponentially in the past decade, grounded in a powerful combination of novel sequencing technologies, bioinformatic approaches, data-sharing networks, and metadata harmonization efforts. This practice report examines recent advances in genomic epidemiology as applied to food safety programs and delineates State, Tribal, Local, and Territorial infrastructure necessary for continued life-saving improvements in public health.
Program: National databases of foodborne pathogen genomes, along with data sharing and evaluation networks such as GenomeTrakr and PulseNet, have transformed how connections are made among isolates and how root causes of outbreaks are determined, allowing much more timely interventions to protect public health.
Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.
Accid Anal Prev
January 2025
School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK.
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technologies face significant challenges in handling spatiotemporal data and multi-feature fusion, including difficulties in big data processing, and have room for improvement in these areas. To address these issues, this paper proposes a novel method that combines autoencoders, Mahalanobis distance, and dynamic Bayesian networks for anomaly detection.
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